Femtosecond X-ray pulse lasers are promising probes for the elucidation of the multiconformational states of biomolecules because they enable snapshots of single biomolecules to be observed as coherent diffraction images. Multi-image processing using an X-ray free-electron laser has proven to be a successful structural analysis method for viruses. However, the performance of single-particle analysis (SPA) for flexible biomolecules with sizes ≤100 nm remains difficult. Owing to the multiconformational states of biomolecules and noisy character of diffraction images, diffraction image improvement by multi-image processing is often ineffective for such molecules. Herein, a single-image super-resolution (SR) model was constructed using an SR convolutional neural network (SRCNN). Data preparation was performed in silico to consider the actual observation situation with unknown molecular orientations and the fluctuation of molecular structure and incident X-ray intensity. It was demonstrated that the trained SRCNN model improved the single-particle diffraction image quality, corresponding to an observed image with an incident X-ray intensity (approximately three to seven times higher than the original X-ray intensity), while retaining the individuality of the diffraction images. The feasibility of SPA for flexible biomolecules with sizes ≤100 nm was dramatically increased by introducing the SRCNN improvement at the beginning of the various structural analysis schemes.

中文翻译：

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使用卷积神经网络对 X 射线单粒子衍射图像的单图像超分辨率改进

飞秒 X 射线脉冲激光器是用于阐明生物分子的多构象状态的有前途的探针，因为它们能够将单个生物分子的快照作为相干衍射图像进行观察。使用 X 射线自由电子激光器的多图像处理已被证明是一种成功的病毒结构分析方法。然而，对于尺寸≤100 nm 的柔性生物分子，单粒子分析 (SPA) 的性能仍然很困难。由于生物分子的多构象状态和衍射图像的噪声特性，多图像处理对衍射图像的改进通常对此类分子无效。在此，使用 SR 卷积神经网络 (SRCNN) 构建了单图像超分辨率 (SR) 模型。数据准备在计算机上进行，以考虑分子取向未知的实际观察情况以及分子结构和入射 X 射线强度的波动。结果表明，经过训练的 SRCNN 模型提高了单粒子衍射图像质量，对应于具有入射 X 射线强度（大约比原始 X 射线强度高 3 到 7 倍）的观察图像，同时保留了衍射图像。通过在各种结构分析方案开始时引入 SRCNN 改进，SPA 对尺寸≤100 nm 的柔性生物分子的可行性显着提高。结果表明，经过训练的 SRCNN 模型提高了单粒子衍射图像质量，对应于具有入射 X 射线强度（大约比原始 X 射线强度高 3 到 7 倍）的观察图像，同时保留了衍射图像。通过在各种结构分析方案开始时引入 SRCNN 改进，SPA 对尺寸≤100 nm 的柔性生物分子的可行性显着提高。结果表明，经过训练的 SRCNN 模型提高了单粒子衍射图像质量，对应于具有入射 X 射线强度（大约比原始 X 射线强度高 3 到 7 倍）的观察图像，同时保留了衍射图像。通过在各种结构分析方案开始时引入 SRCNN 改进，SPA 对尺寸≤100 nm 的柔性生物分子的可行性显着提高。